DocumentCode :
13883
Title :
Optimization of Advertising Budget Allocation Over Time Based on LS-SVMR and DE
Author :
Dapeng Niu ; Ying Sun ; Fuli Wang
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Volume :
11
Issue :
4
fYear :
2014
fDate :
Oct. 2014
Firstpage :
1076
Lastpage :
1082
Abstract :
The advertising budget allocation problem for financial service is dealt with based on statistical learning and evolutionary computation in this paper. Taking the carry-over effects of the advertising into account, the least squares support vector machine regression (LS-SVMR) is used to construct the response model. A comparison between the proposed response model and traditional regression method based market response models is implemented. The results show the effectiveness and validity of the former model. Taking the budgets allocated to every month in the planning horizon as decision variables, the budget allocation optimization model is built and an improved differential evolution algorithm is used to find the optimal solutions. Finally, the proposed budget allocation method is illustrated by a practical problem.
Keywords :
budgeting; evolutionary computation; least squares approximations; regression analysis; support vector machines; DE; LS-SVMR; advertising budget allocation problem; decision variables; differential evolution; evolutionary computation; financial service; least squares support vector machine regression; market response model; planning horizon; regression method; statistical learning; Advertising; Evolutionary computation; Least squares methods; Optimization; Resource management; Support vector machines; Advertising budget allocation; differential evolution algorithm; least squares support vector machine regression (LS-SVMR); optimization;
fLanguage :
English
Journal_Title :
Automation Science and Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1545-5955
Type :
jour
DOI :
10.1109/TASE.2013.2279801
Filename :
6601736
Link To Document :
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